code: def test_inverse_transform_exp_no_default(exp_base, df_vartypes):
      transformer = PowerTransformer(exp=exp_base)
      Xt = transformer.fit_transform(df_vartypes)
      X = transformer.inverse_transform(Xt)
  
      # convert numbers to original format.
      X["Age"] = X["Age"].round().astype("int64")
      X["Marks"] = X["Marks"].round(1)
  
      # test init params
      # assert transformer.exp == 100
      assert transformer.variables is None
      # test fit attr
      assert transformer.variables_ == ["Age", "Marks"]
      assert transformer.n_features_in_ == 5
      # test transform output
      pd.testing.assert_frame_equal(X, df_vartypes)
  
file_path: feature_engine/tests/test_transformation/test_power_transformer.py
imports: import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.transformation import PowerTransformer
label_desc: Use image node_id 6 for calling a global function with example usage: test_inverse_transform_exp_no_default(exp_base, df_vartypes) without return types